import pandas as pd
from sklearn.model_selection import train_test_split
import joblib
import numpy as np
from sklearn.feature_selection import VarianceThreshold, SelectKBest, f_classif

# Show all columns in the DataFrame
pd.set_option('display.max_columns', None)
pd.set_option('display.width', None)

# Load raw data
#benign = pd.read_csv('datasets/hmi_normal_6h_flow_label.csv')
scapy_modify = pd.read_csv('datasets/mitm_hmi_scapy_modify_1plc_6h_flow_label.csv')
fw_36plc = pd.read_csv('datasets/mitm_hmi_forward_36plc_6h_flow_label.csv')

scapy_modify.groupby("Label").describe()

fw_36plc['Label'].unique()

array(['mitm'], dtype=object)

fw_36plc['Label'] = 'mitm_36plc'

# Drop unnecessary columns
cols_to_drop = ['Flow ID', 'Src IP', 'Src Port', 'Dst IP', 'Dst Port', 'Timestamp']
#benign.drop(columns=cols_to_drop, errors='ignore', inplace=True)
scapy_modify.drop(columns=cols_to_drop, errors='ignore', inplace=True)
fw_36plc.drop(columns=cols_to_drop,errors='ignore', inplace=True)

# Merge
df = pd.concat([scapy_modify,fw_36plc], ignore_index=True)

df.groupby("Label").describe()

import seaborn as sns
import matplotlib.pyplot as plt

for col in df.select_dtypes(include='number').columns:
    plt.figure(figsize=(12, 4))
    sns.boxplot(y='Label', x=col, data=df)
    plt.title(f'Boxplot of {col} by Label')
    plt.show()

for col in df.select_dtypes(include='number').columns:
    plt.figure(figsize=(12, 4))
    sns.violinplot(y='Label', x=col, data=df)
    plt.title(f'Violin plot of {col} by Label')
    plt.show()

from scipy.stats import ttest_ind

label_values = df['Label'].unique()
group1 = df[df['Label'] == label_values[0]]
group2 = df[df['Label'] == label_values[1]]

for col in df.select_dtypes(include='number').columns:
    stat, p = ttest_ind(group1[col], group2[col], nan_policy='omit')
    print(f'{col}: t={stat:.2f}, p={p:.4f}')

Protocol: t=nan, p=nan
Flow Duration: t=-21.20, p=0.0000
Tot Fwd Pkts: t=0.35, p=0.7259
Tot Bwd Pkts: t=-0.60, p=0.5465
TotLen Fwd Pkts: t=0.32, p=0.7456
TotLen Bwd Pkts: t=0.40, p=0.6891
Fwd Pkt Len Max: t=0.53, p=0.5948
Fwd Pkt Len Min: t=nan, p=nan
Fwd Pkt Len Mean: t=-0.00, p=0.9984
Fwd Pkt Len Std: t=0.38, p=0.7070
Bwd Pkt Len Max: t=0.63, p=0.5314
Bwd Pkt Len Min: t=nan, p=nan
Bwd Pkt Len Mean: t=0.83, p=0.4080
Bwd Pkt Len Std: t=0.65, p=0.5180
Flow Byts/s: t=73.69, p=0.0000
Flow Pkts/s: t=37.37, p=0.0000
Flow IAT Mean: t=-25.84, p=0.0000
Flow IAT Std: t=-9.07, p=0.0000
Flow IAT Max: t=-6.88, p=0.0000
Flow IAT Min: t=-11.43, p=0.0000
Fwd IAT Tot: t=-316.62, p=0.0000
Fwd IAT Mean: t=-315.29, p=0.0000
Fwd IAT Std: t=-283.50, p=0.0000
Fwd IAT Max: t=-273.95, p=0.0000
Fwd IAT Min: t=-108.79, p=0.0000
Bwd IAT Tot: t=-21.18, p=0.0000
Bwd IAT Mean: t=-35.93, p=0.0000
Bwd IAT Std: t=-6.34, p=0.0000
Bwd IAT Max: t=-7.33, p=0.0000
Bwd IAT Min: t=-333.73, p=0.0000
Fwd PSH Flags: t=nan, p=nan
Bwd PSH Flags: t=nan, p=nan
Fwd URG Flags: t=nan, p=nan
Bwd URG Flags: t=nan, p=nan
Fwd Header Len: t=0.25, p=0.7998
Bwd Header Len: t=-0.40, p=0.6892
Fwd Pkts/s: t=73.45, p=0.0000
Bwd Pkts/s: t=37.32, p=0.0000
Pkt Len Min: t=nan, p=nan
Pkt Len Max: t=-0.26, p=0.7954
Pkt Len Mean: t=0.37, p=0.7113
Pkt Len Std: t=0.28, p=0.7759
Pkt Len Var: t=0.57, p=0.5680
FIN Flag Cnt: t=0.06, p=0.9483
SYN Flag Cnt: t=0.01, p=0.9946
RST Flag Cnt: t=nan, p=nan
PSH Flag Cnt: t=nan, p=nan
ACK Flag Cnt: t=-0.01, p=0.9946
URG Flag Cnt: t=nan, p=nan
CWE Flag Count: t=nan, p=nan
ECE Flag Cnt: t=nan, p=nan
Down/Up Ratio: t=-0.03, p=0.9793
Pkt Size Avg: t=0.37, p=0.7107
Fwd Seg Size Avg: t=-0.00, p=0.9984
Bwd Seg Size Avg: t=0.83, p=0.4080
Fwd Byts/b Avg: t=nan, p=nan
Fwd Pkts/b Avg: t=nan, p=nan
Fwd Blk Rate Avg: t=nan, p=nan
Bwd Byts/b Avg: t=nan, p=nan
Bwd Pkts/b Avg: t=nan, p=nan
Bwd Blk Rate Avg: t=nan, p=nan
Subflow Fwd Pkts: t=0.35, p=0.7259
Subflow Fwd Byts: t=0.32, p=0.7456
Subflow Bwd Pkts: t=-0.60, p=0.5465
Subflow Bwd Byts: t=0.40, p=0.6891
Init Fwd Win Byts: t=nan, p=nan
Init Bwd Win Byts: t=1.83, p=0.0675
Fwd Act Data Pkts: t=-0.04, p=0.9661
Fwd Seg Size Min: t=nan, p=nan
Active Mean: t=-1.34, p=0.1815
Active Std: t=nan, p=nan
Active Max: t=-1.34, p=0.1815
Active Min: t=-1.34, p=0.1815
Idle Mean: t=-0.29, p=0.7725
Idle Std: t=nan, p=nan
Idle Max: t=-0.29, p=0.7725
Idle Min: t=-0.29, p=0.7725

/home/ics-security/anaconda3/envs/DATN/lib/python3.9/site-packages/scipy/stats/_axis_nan_policy.py:531: RuntimeWarning: Precision loss occurred in moment calculation due to catastrophic cancellation. This occurs when the data are nearly identical. Results may be unreliable.
  res = hypotest_fun_out(*samples, **kwds)

# from sklearn.preprocessing import LabelEncoder

# # Create and fit the encoder
# le = LabelEncoder()
# df['Label_encoded'] = le.fit_transform(df['Label'])

# # Create mapping dictionary
# label_mapping = dict(zip(le.classes_, le.transform(le.classes_)))

# print("Label to Integer Mapping:")
# for label, code in label_mapping.items():
#     print(f"'{label}' → {code}")

Label to Integer Mapping:
'mitm' → 0
'mitm_36plc' → 1
'normal' → 2

# reverse_mapping = dict(zip(le.transform(le.classes_), le.classes_))

# print("\nInteger to Label Mapping:")
# for code, label in reverse_mapping.items():
#     print(f"{code} → '{label}'")

Integer to Label Mapping:
0 → 'mitm'
1 → 'mitm_36plc'
2 → 'normal'

	Src Port								Dst Port								Protocol								Flow Duration								Tot Fwd Pkts								Tot Bwd Pkts								TotLen Fwd Pkts								TotLen Bwd Pkts								Fwd Pkt Len Max								Fwd Pkt Len Min								Fwd Pkt Len Mean								Fwd Pkt Len Std								Bwd Pkt Len Max								Bwd Pkt Len Min								Bwd Pkt Len Mean								Bwd Pkt Len Std								Flow Byts/s								Flow Pkts/s								Flow IAT Mean								Flow IAT Std								Flow IAT Max								Flow IAT Min								Fwd IAT Tot								Fwd IAT Mean								Fwd IAT Std								Fwd IAT Max								Fwd IAT Min								Bwd IAT Tot								Bwd IAT Mean								Bwd IAT Std								Bwd IAT Max								Bwd IAT Min								Fwd PSH Flags								Bwd PSH Flags								Fwd URG Flags								Bwd URG Flags								Fwd Header Len								Bwd Header Len								Fwd Pkts/s								Bwd Pkts/s								Pkt Len Min								Pkt Len Max								Pkt Len Mean								Pkt Len Std								Pkt Len Var								FIN Flag Cnt								SYN Flag Cnt								RST Flag Cnt								PSH Flag Cnt								ACK Flag Cnt								URG Flag Cnt								CWE Flag Count								ECE Flag Cnt								Down/Up Ratio								Pkt Size Avg								Fwd Seg Size Avg								Bwd Seg Size Avg								Fwd Byts/b Avg								Fwd Pkts/b Avg								Fwd Blk Rate Avg								Bwd Byts/b Avg								Bwd Pkts/b Avg								Bwd Blk Rate Avg								Subflow Fwd Pkts								Subflow Fwd Byts								Subflow Bwd Pkts								Subflow Bwd Byts								Init Fwd Win Byts								Init Bwd Win Byts								Fwd Act Data Pkts								Fwd Seg Size Min								Active Mean								Active Std								Active Max								Active Min								Idle Mean								Idle Std								Idle Max								Idle Min
	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max
Label
mitm	6754.0	45706.734972	5553.484326	32784.0	44818.0	44818.0	45037.0	60992.0	6754.0	45878.698253	6111.837581	32784.0	44818.0	44818.0	47685.5	60992.0	6754.0	6.0	0.0	6.0	6.0	6.0	6.0	6.0	6754.0	434630.275540	1.566391e+06	14.0	35.0	616202.5	792774.25	99088176.0	6754.0	2.449067	2.457426	0.0	0.0	4.0	5.0	6.0	6754.0	3.553154	1.569620	1.0	2.0	5.0	5.0	8.0	6754.0	47.787385	48.099579	0.0	0.0	72.0	98.0	168.0	6754.0	38.269174	38.660947	0.0	0.0	72.0	72.0	100.0	6754.0	33.752147	34.166059	0.0	0.0	44.0	70.0	72.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	9.749585	9.755739	0.0	0.0	18.0	19.6	28.0	6754.0	14.920295	15.028194	0.0	0.0	21.786846	30.672463	34.292856	6754.0	24.265028	24.886134	0.0	0.0	44.0	44.0	72.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	7.480942	7.496550	0.0	0.0	12.375	14.4	16.666667	6754.0	11.012655	11.146532	0.0	0.0	20.51341	20.513410	29.330303	6754.0	106.448680	107.724388	0.0	0.0	1.992790	216.632122	338.550777	6754.0	35418.533351	39916.649455	0.121104	12.613931	16.231172	57142.857143	142857.142857	6754.0	47810.307408	144692.168035	14.0	35.0	69502.5	88088.583333	9.008016e+06	6754.0	61929.003762	455455.016393	0.0	0.0	75823.085052	105804.078147	2.963342e+07	6754.0	165512.691146	1.508231e+06	14.0	35.0	194066.0	276949.75	98355743.0	6754.0	63.708617	1664.419176	13.0	20.0	29.0	38.0	100501.0	6754.0	314562.587060	315999.420297	0.0	0.0	470988.5	628555.0	776518.0	6754.0	81354.608528	82457.804395	0.0	0.0	118766.25	158968.375	252569.00	6754.0	74244.508187	75455.695403	0.0	0.0	65767.341155	151067.292561	201558.904417	6754.0	154264.025318	155730.636886	0.0	0.0	204687.0	307223.25	438777.0	6754.0	6640.931744	18928.241434	0.0	0.0	1958.0	6095.25	135708.0	6754.0	431217.406574	1.565578e+06	0.0	35.0	609929.0	785992.25	99088176.0	6754.0	102895.405747	237557.336597	0.0	35.0	126171.9	194004.9125	1.415545e+07	6754.0	60112.545143	569092.745766	0.0	0.0	57030.169689	98073.563059	3.712901e+07	6754.0	173616.759994	1.508831e+06	0.0	35.0	213070.0	293905.25	98355743.0	6754.0	38636.816849	43667.114064	0.0	35.0	105.5	81205.25	151454.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	78.790643	78.922803	0.0	0.0	136.0	160.0	192.0	6754.0	121.288126	57.548323	44.0	64.0	176.0	176.0	264.0	6754.0	3.035348	3.084742	0.0	0.0	3.770851	6.213025	15.614265	6754.0	35415.498003	39919.342230	0.080736	6.368036	9.511096	57142.857143	142857.142857	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	35.010364	35.021639	0.0	0.0	68.0	70.0	72.0	6754.0	7.821808	7.821432	0.0	0.0	13.153846	15.636364	20.000000	6754.0	12.154557	12.152875	0.0	0.0	22.905756	24.371369	27.804512	6754.0	295.403750	295.439760	0.0	0.0	524.717949	593.963636	773.090909	6754.0	0.499704	0.500037	0.0	0.0	0.0	1.0	1.0	6754.0	0.499852	0.500037	0.0	0.0	0.0	1.0	1.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.500148	0.500037	0.0	0.0	1.0	1.0	1.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.500444	0.500629	0.0	0.0	1.0	1.0	2.0	6754.0	8.603843	8.603407	0.0	0.0	14.25	17.2	21.818182	6754.0	9.749585	9.755739	0.0	0.0	18.0	19.6	28.0	6754.0	7.480942	7.496550	0.0	0.0	12.375	14.4	16.666667	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	2.449067	2.457426	0.0	0.0	4.0	5.0	6.0	6754.0	47.787385	48.099579	0.0	0.0	72.0	98.0	168.0	6754.0	3.553154	1.569620	1.0	2.0	5.0	5.0	8.0	6754.0	38.269174	38.660947	0.0	0.0	72.0	72.0	100.0	6754.0	-1.0	0.0	-1.0	-1.0	-1.0	-1.0	-1.0	6754.0	83.896062	0.994657	83.0	83.0	83.0	85.0	85.0	6754.0	1.000740	1.000740	0.0	0.0	2.0	2.0	3.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.008884	0.549823	0.0	0.0	0.0	0.0	41.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.008884	0.549823	0.0	0.0	0.0	0.0	41.0	6754.0	0.008884	0.549823	0.0	0.0	0.0	0.0	41.0	6754.0	25647.077584	1.503937e+06	0.0	0.0	0.0	0.0	98355743.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	25647.077584	1.503937e+06	0.0	0.0	0.0	0.0	98355743.0	6754.0	25647.077584	1.503937e+06	0.0	0.0	0.0	0.0	98355743.0
normal	164457.0	45785.487161	5607.404711	32768.0	44818.0	44818.0	45764.0	60998.0	164457.0	45946.057510	6071.042539	32768.0	44818.0	44818.0	48036.0	60998.0	164457.0	6.0	0.0	6.0	6.0	6.0	6.0	6.0	164457.0	58148.334805	1.424615e+06	7.0	14.0	57859.0	73380.00	117511126.0	164457.0	2.459804	2.466897	0.0	0.0	4.0	5.0	6.0	164457.0	3.541515	1.553819	2.0	2.0	5.0	5.0	8.0	164457.0	47.981515	48.193465	0.0	0.0	72.0	96.0	100.0	164457.0	38.461665	38.756286	0.0	0.0	72.0	78.0	100.0	164457.0	33.978535	34.284204	0.0	0.0	44.0	68.0	72.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	9.749339	9.753269	0.0	0.0	18.0	19.2	20.0	164457.0	14.990621	15.069873	0.0	0.0	21.786846	29.852973	31.496031	164457.0	24.458685	24.926832	0.0	0.0	44.0	50.0	72.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	7.558702	7.572162	0.0	0.0	12.000	15.6	16.666667	164457.0	11.102558	11.203735	0.0	0.0	20.51341	22.733236	29.330303	164457.0	1164.924351	1180.243370	0.0	0.0	1.803155	2355.486778	3057.083121	164457.0	71186.095216	78249.038332	0.102118	136.278772	172.962502	142857.142857	285714.285714	164457.0	6053.155641	129522.082678	7.0	14.0	6424.0	8153.222222	1.068283e+07	164457.0	13498.581455	429158.498273	0.0	0.0	11627.964869	13719.697409	3.540754e+07	164457.0	43585.339639	1.423458e+06	7.0	14.0	36986.0	43238.00	117440559.0	164457.0	16.784807	9.151835	4.0	11.0	14.0	22.0	2064.0	164457.0	34062.665639	34647.273340	0.0	0.0	50543.0	66317.0	156975.0	164457.0	8727.146386	8898.843536	0.0	0.0	13176.00	16922.000	39243.75	164457.0	10256.294977	10501.460605	0.0	0.0	14713.764316	19285.950368	68549.944913	164457.0	23079.325629	23513.684397	0.0	0.0	37016.0	43284.00	141872.0	164457.0	1221.682902	1431.210742	0.0	0.0	1239.0	2082.00	19406.0	164457.0	55162.797917	1.424580e+06	7.0	14.0	54144.0	67067.00	117511126.0	164457.0	11443.127877	203580.924270	7.0	14.0	11946.6	16542.2500	1.678730e+07	164457.0	17682.778109	537956.338481	0.0	0.0	14333.896201	18761.503636	4.438392e+07	164457.0	43794.498726	1.423459e+06	7.0	14.0	37471.0	43664.00	117440559.0	164457.0	1716.652025	2087.730052	7.0	14.0	103.0	3182.00	13849.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	79.039846	79.159871	0.0	0.0	136.0	160.0	192.0	164457.0	121.004080	57.193933	64.0	64.0	176.0	176.0	264.0	164457.0	33.152261	33.689838	0.0	0.0	0.041677	67.281168	96.677516	164457.0	71152.942954	78279.141975	0.068079	68.809865	100.446989	142857.142857	285714.285714	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	34.897913	34.918514	0.0	0.0	66.0	68.0	72.0	164457.0	7.857901	7.856737	0.0	0.0	13.384615	15.636364	15.818182	164457.0	12.197651	12.195516	0.0	0.0	23.027297	24.371369	24.491928	164457.0	297.512394	297.490619	0.0	0.0	530.256410	593.963636	599.854545	164457.0	0.500106	0.500002	0.0	0.0	1.0	1.0	1.0	164457.0	0.499894	0.500002	0.0	0.0	0.0	1.0	1.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.500106	0.500002	0.0	0.0	1.0	1.0	1.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.500283	0.500427	0.0	0.0	1.0	1.0	2.0	164457.0	8.643638	8.642374	0.0	0.0	14.50	17.2	17.400000	164457.0	9.749339	9.753269	0.0	0.0	18.0	19.2	20.0	164457.0	7.558702	7.572162	0.0	0.0	12.000	15.6	16.666667	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	2.459804	2.466897	0.0	0.0	4.0	5.0	6.0	164457.0	47.981515	48.193465	0.0	0.0	72.0	96.0	100.0	164457.0	3.541515	1.553819	2.0	2.0	5.0	5.0	8.0	164457.0	38.461665	38.756286	0.0	0.0	72.0	78.0	100.0	164457.0	-1.0	0.0	-1.0	-1.0	-1.0	-1.0	-1.0	164457.0	83.918684	0.996691	83.0	83.0	83.0	85.0	85.0	164457.0	1.000213	1.000003	0.0	0.0	2.0	2.0	2.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.003867	0.287735	0.0	0.0	0.0	0.0	36.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.003867	0.287735	0.0	0.0	0.0	0.0	36.0	164457.0	0.003867	0.287735	0.0	0.0	0.0	0.0	36.0	164457.0	20526.033231	1.423597e+06	0.0	0.0	0.0	0.0	117440559.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	20526.033231	1.423597e+06	0.0	0.0	0.0	0.0	117440559.0	164457.0	20526.033231	1.423597e+06	0.0	0.0	0.0	0.0	117440559.0

	Protocol								Flow Duration								Tot Fwd Pkts								Tot Bwd Pkts								TotLen Fwd Pkts								TotLen Bwd Pkts								Fwd Pkt Len Max								Fwd Pkt Len Min								Fwd Pkt Len Mean								Fwd Pkt Len Std								Bwd Pkt Len Max								Bwd Pkt Len Min								Bwd Pkt Len Mean								Bwd Pkt Len Std								Flow Byts/s								Flow Pkts/s								Flow IAT Mean								Flow IAT Std								Flow IAT Max								Flow IAT Min								Fwd IAT Tot								Fwd IAT Mean								Fwd IAT Std								Fwd IAT Max								Fwd IAT Min								Bwd IAT Tot								Bwd IAT Mean								Bwd IAT Std								Bwd IAT Max								Bwd IAT Min								Fwd PSH Flags								Bwd PSH Flags								Fwd URG Flags								Bwd URG Flags								Fwd Header Len								Bwd Header Len								Fwd Pkts/s								Bwd Pkts/s								Pkt Len Min								Pkt Len Max								Pkt Len Mean								Pkt Len Std								Pkt Len Var								FIN Flag Cnt								SYN Flag Cnt								RST Flag Cnt								PSH Flag Cnt								ACK Flag Cnt								URG Flag Cnt								CWE Flag Count								ECE Flag Cnt								Down/Up Ratio								Pkt Size Avg								Fwd Seg Size Avg								Bwd Seg Size Avg								Fwd Byts/b Avg								Fwd Pkts/b Avg								Fwd Blk Rate Avg								Bwd Byts/b Avg								Bwd Pkts/b Avg								Bwd Blk Rate Avg								Subflow Fwd Pkts								Subflow Fwd Byts								Subflow Bwd Pkts								Subflow Bwd Byts								Init Fwd Win Byts								Init Bwd Win Byts								Fwd Act Data Pkts								Fwd Seg Size Min								Active Mean								Active Std								Active Max								Active Min								Idle Mean								Idle Std								Idle Max								Idle Min
	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max	count	mean	std	min	25%	50%	75%	max
Label
mitm	6754.0	6.0	0.0	6.0	6.0	6.0	6.0	6.0	6754.0	434630.275540	1.566391e+06	14.0	35.0	616202.5	792774.25	99088176.0	6754.0	2.449067	2.457426	0.0	0.0	4.0	5.0	6.0	6754.0	3.553154	1.569620	1.0	2.0	5.0	5.0	8.0	6754.0	47.787385	48.099579	0.0	0.0	72.0	98.0	168.0	6754.0	38.269174	38.660947	0.0	0.0	72.0	72.0	100.0	6754.0	33.752147	34.166059	0.0	0.0	44.0	70.0	72.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	9.749585	9.755739	0.0	0.0	18.0	19.6	28.0	6754.0	14.920295	15.028194	0.0	0.0	21.786846	30.672463	34.292856	6754.0	24.265028	24.886134	0.0	0.0	44.0	44.0	72.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	7.480942	7.496550	0.0	0.0	12.375	14.4	16.666667	6754.0	11.012655	11.146532	0.0	0.0	20.51341	20.513410	29.330303	6754.0	106.448680	107.724388	0.0	0.0	1.992790	216.632122	338.550777	6754.0	35418.533351	39916.649455	0.121104	12.613931	16.231172	57142.857143	142857.142857	6754.0	47810.307408	144692.168035	14.0	35.0	69502.500000	88088.583333	9.008016e+06	6754.0	61929.003762	455455.016393	0.0	0.0	75823.085052	105804.078147	2.963342e+07	6754.0	165512.691146	1.508231e+06	14.0	35.0	194066.0	276949.75	98355743.0	6754.0	63.708617	1664.419176	13.0	20.0	29.0	38.0	100501.0	6754.0	314562.587060	315999.420297	0.0	0.0	470988.5	628555.0	776518.0	6754.0	81354.608528	82457.804395	0.0	0.0	118766.25	158968.375	252569.00	6754.0	74244.508187	75455.695403	0.0	0.0	65767.341155	151067.292561	201558.904417	6754.0	154264.025318	155730.636886	0.0	0.0	204687.0	307223.25	438777.0	6754.0	6640.931744	18928.241434	0.0	0.0	1958.0	6095.25	135708.0	6754.0	431217.406574	1.565578e+06	0.0	35.0	609929.0	785992.25	99088176.0	6754.0	102895.405747	237557.336597	0.0	35.0	126171.9	194004.9125	1.415545e+07	6754.0	60112.545143	569092.745766	0.0	0.0	57030.169689	98073.563059	3.712901e+07	6754.0	173616.759994	1.508831e+06	0.0	35.0	213070.0	293905.25	98355743.0	6754.0	38636.816849	43667.114064	0.0	35.0	105.5	81205.25	151454.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	78.790643	78.922803	0.0	0.0	136.0	160.0	192.0	6754.0	121.288126	57.548323	44.0	64.0	176.0	176.0	264.0	6754.0	3.035348	3.084742	0.0	0.0	3.770851	6.213025	15.614265	6754.0	35415.498003	39919.342230	0.080736	6.368036	9.511096	57142.857143	142857.142857	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	35.010364	35.021639	0.0	0.0	68.0	70.0	72.0	6754.0	7.821808	7.821432	0.0	0.0	13.153846	15.636364	20.000000	6754.0	12.154557	12.152875	0.0	0.0	22.905756	24.371369	27.804512	6754.0	295.403750	295.439760	0.0	0.0	524.717949	593.963636	773.090909	6754.0	0.499704	0.500037	0.0	0.0	0.0	1.0	1.0	6754.0	0.499852	0.500037	0.0	0.0	0.0	1.0	1.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.500148	0.500037	0.0	0.0	1.0	1.0	1.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.500444	0.500629	0.0	0.0	1.0	1.0	2.0	6754.0	8.603843	8.603407	0.0	0.0	14.25	17.2	21.818182	6754.0	9.749585	9.755739	0.0	0.0	18.0	19.6	28.0	6754.0	7.480942	7.496550	0.0	0.0	12.375	14.4	16.666667	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	2.449067	2.457426	0.0	0.0	4.0	5.0	6.0	6754.0	47.787385	48.099579	0.0	0.0	72.0	98.0	168.0	6754.0	3.553154	1.569620	1.0	2.0	5.0	5.0	8.0	6754.0	38.269174	38.660947	0.0	0.0	72.0	72.0	100.0	6754.0	-1.0	0.0	-1.0	-1.0	-1.0	-1.0	-1.0	6754.0	83.896062	0.994657	83.0	83.0	83.0	85.0	85.0	6754.0	1.000740	1.000740	0.0	0.0	2.0	2.0	3.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.008884	0.549823	0.0	0.0	0.0	0.0	41.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	0.008884	0.549823	0.0	0.0	0.0	0.0	41.0	6754.0	0.008884	0.549823	0.0	0.0	0.0	0.0	41.0	6754.0	25647.077584	1.503937e+06	0.0	0.0	0.0	0.0	98355743.0	6754.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	6754.0	25647.077584	1.503937e+06	0.0	0.0	0.0	0.0	98355743.0	6754.0	25647.077584	1.503937e+06	0.0	0.0	0.0	0.0	98355743.0
mitm_36plc	188383.0	6.0	0.0	6.0	6.0	6.0	6.0	6.0	188383.0	65592.658149	1.536137e+06	5.0	11.0	60558.0	78157.50	119999986.0	188383.0	2.456639	2.464104	0.0	0.0	4.0	5.0	6.0	188383.0	3.545108	1.558325	2.0	2.0	5.0	5.0	8.0	188383.0	47.905904	48.129617	0.0	0.0	72.0	96.0	100.0	188383.0	38.543924	38.853495	0.0	0.0	72.0	78.0	100.0	188383.0	33.901817	34.226893	0.0	0.0	44.0	68.0	72.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	9.746797	9.750116	0.0	0.0	18.0	19.2	25.0	188383.0	14.965210	15.048824	0.0	0.0	21.786846	29.852973	34.000000	188383.0	24.539836	25.033469	0.0	0.0	44.0	50.0	72.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	7.563971	7.577124	0.0	0.0	12.000	15.6	16.666667	188383.0	11.127344	11.233186	0.0	0.0	20.51341	22.733236	29.330303	188383.0	1094.954881	1109.816059	0.0	0.0	2.007809	2210.650760	2991.746905	188383.0	90833.995794	99095.427321	0.100000	127.946774	165.130949	181818.181818	400000.000000	188383.0	6776.849563	139659.181256	5.0	11.0	6728.666667	8684.166667	1.090909e+07	188383.0	15207.344502	462689.885739	0.0	0.0	11859.989497	14094.021412	3.615716e+07	188383.0	49186.555385	1.534704e+06	5.0	11.0	37497.0	44321.00	119927029.0	188383.0	12.346714	5.497144	4.0	8.0	11.0	16.0	406.0	188383.0	34614.072215	35220.837825	0.0	0.0	51083.0	67361.0	229220.0	188383.0	8885.135330	9062.045093	0.0	0.0	13306.00	17228.750	57305.00	188383.0	10548.331855	10815.442744	0.0	0.0	15065.157716	19836.705001	99892.936230	188383.0	23655.525148	24129.986474	0.0	0.0	37500.0	44366.00	206711.0	188383.0	1217.281368	1417.517579	0.0	0.0	1204.0	2085.00	16531.0	188383.0	62640.287871	1.536110e+06	5.0	11.0	56631.0	72129.00	119999986.0	188383.0	12749.303370	219509.307229	5.0	11.0	12548.0	17757.5000	1.714286e+07	188383.0	19601.336573	579979.910079	0.0	0.0	14100.013163	18751.943017	4.532356e+07	188383.0	49405.281543	1.534704e+06	5.0	11.0	37921.0	44752.50	119927029.0	188383.0	1750.352845	2193.890666	5.0	11.0	65.0	2841.00	14882.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	78.965214	79.089035	0.0	0.0	136.0	160.0	192.0	188383.0	121.093007	57.296271	64.0	64.0	176.0	176.0	264.0	188383.0	31.116261	31.636463	0.0	0.0	0.046454	62.969913	87.624500	188383.0	90802.879533	99123.910254	0.066667	64.648763	95.632770	181818.181818	400000.000000	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	34.898733	34.916479	0.0	0.0	66.0	68.0	72.0	188383.0	7.858376	7.856614	0.0	0.0	13.384615	15.636364	17.200000	188383.0	12.198329	12.195228	0.0	0.0	23.027297	24.371369	25.231374	188383.0	297.522027	297.476984	0.0	0.0	530.256410	593.963636	636.622222	188383.0	0.500141	0.500001	0.0	0.0	1.0	1.0	1.0	188383.0	0.499859	0.500001	0.0	0.0	0.0	1.0	1.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.500141	0.500001	0.0	0.0	1.0	1.0	1.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.500422	0.500574	0.0	0.0	1.0	1.0	2.0	188383.0	8.644150	8.642232	0.0	0.0	14.50	17.2	19.111111	188383.0	9.746797	9.750116	0.0	0.0	18.0	19.2	25.0	188383.0	7.563971	7.577124	0.0	0.0	12.000	15.6	16.666667	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	2.456639	2.464104	0.0	0.0	4.0	5.0	6.0	188383.0	47.905904	48.129617	0.0	0.0	72.0	96.0	100.0	188383.0	3.545108	1.558325	2.0	2.0	5.0	5.0	8.0	188383.0	38.543924	38.853495	0.0	0.0	72.0	78.0	100.0	188383.0	-1.0	0.0	-1.0	-1.0	-1.0	-1.0	-1.0	188383.0	83.912099	0.996132	83.0	83.0	83.0	85.0	85.0	188383.0	1.000292	1.000003	0.0	0.0	2.0	2.0	2.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.003668	0.236835	0.0	0.0	0.0	0.0	27.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	0.003668	0.236835	0.0	0.0	0.0	0.0	27.0	188383.0	0.003668	0.236835	0.0	0.0	0.0	0.0	27.0	188383.0	25559.405679	1.534908e+06	0.0	0.0	0.0	0.0	119927029.0	188383.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	188383.0	25559.405679	1.534908e+06	0.0	0.0	0.0	0.0	119927029.0	188383.0	25559.405679	1.534908e+06	0.0	0.0	0.0	0.0	119927029.0
normal	164457.0	6.0	0.0	6.0	6.0	6.0	6.0	6.0	164457.0	58148.334805	1.424615e+06	7.0	14.0	57859.0	73380.00	117511126.0	164457.0	2.459804	2.466897	0.0	0.0	4.0	5.0	6.0	164457.0	3.541515	1.553819	2.0	2.0	5.0	5.0	8.0	164457.0	47.981515	48.193465	0.0	0.0	72.0	96.0	100.0	164457.0	38.461665	38.756286	0.0	0.0	72.0	78.0	100.0	164457.0	33.978535	34.284204	0.0	0.0	44.0	68.0	72.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	9.749339	9.753269	0.0	0.0	18.0	19.2	20.0	164457.0	14.990621	15.069873	0.0	0.0	21.786846	29.852973	31.496031	164457.0	24.458685	24.926832	0.0	0.0	44.0	50.0	72.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	7.558702	7.572162	0.0	0.0	12.000	15.6	16.666667	164457.0	11.102558	11.203735	0.0	0.0	20.51341	22.733236	29.330303	164457.0	1164.924351	1180.243370	0.0	0.0	1.803155	2355.486778	3057.083121	164457.0	71186.095216	78249.038332	0.102118	136.278772	172.962502	142857.142857	285714.285714	164457.0	6053.155641	129522.082678	7.0	14.0	6424.000000	8153.222222	1.068283e+07	164457.0	13498.581455	429158.498273	0.0	0.0	11627.964869	13719.697409	3.540754e+07	164457.0	43585.339639	1.423458e+06	7.0	14.0	36986.0	43238.00	117440559.0	164457.0	16.784807	9.151835	4.0	11.0	14.0	22.0	2064.0	164457.0	34062.665639	34647.273340	0.0	0.0	50543.0	66317.0	156975.0	164457.0	8727.146386	8898.843536	0.0	0.0	13176.00	16922.000	39243.75	164457.0	10256.294977	10501.460605	0.0	0.0	14713.764316	19285.950368	68549.944913	164457.0	23079.325629	23513.684397	0.0	0.0	37016.0	43284.00	141872.0	164457.0	1221.682902	1431.210742	0.0	0.0	1239.0	2082.00	19406.0	164457.0	55162.797917	1.424580e+06	7.0	14.0	54144.0	67067.00	117511126.0	164457.0	11443.127877	203580.924270	7.0	14.0	11946.6	16542.2500	1.678730e+07	164457.0	17682.778109	537956.338481	0.0	0.0	14333.896201	18761.503636	4.438392e+07	164457.0	43794.498726	1.423459e+06	7.0	14.0	37471.0	43664.00	117440559.0	164457.0	1716.652025	2087.730052	7.0	14.0	103.0	3182.00	13849.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	79.039846	79.159871	0.0	0.0	136.0	160.0	192.0	164457.0	121.004080	57.193933	64.0	64.0	176.0	176.0	264.0	164457.0	33.152261	33.689838	0.0	0.0	0.041677	67.281168	96.677516	164457.0	71152.942954	78279.141975	0.068079	68.809865	100.446989	142857.142857	285714.285714	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	34.897913	34.918514	0.0	0.0	66.0	68.0	72.0	164457.0	7.857901	7.856737	0.0	0.0	13.384615	15.636364	15.818182	164457.0	12.197651	12.195516	0.0	0.0	23.027297	24.371369	24.491928	164457.0	297.512394	297.490619	0.0	0.0	530.256410	593.963636	599.854545	164457.0	0.500106	0.500002	0.0	0.0	1.0	1.0	1.0	164457.0	0.499894	0.500002	0.0	0.0	0.0	1.0	1.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.500106	0.500002	0.0	0.0	1.0	1.0	1.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.500283	0.500427	0.0	0.0	1.0	1.0	2.0	164457.0	8.643638	8.642374	0.0	0.0	14.50	17.2	17.400000	164457.0	9.749339	9.753269	0.0	0.0	18.0	19.2	20.0	164457.0	7.558702	7.572162	0.0	0.0	12.000	15.6	16.666667	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	2.459804	2.466897	0.0	0.0	4.0	5.0	6.0	164457.0	47.981515	48.193465	0.0	0.0	72.0	96.0	100.0	164457.0	3.541515	1.553819	2.0	2.0	5.0	5.0	8.0	164457.0	38.461665	38.756286	0.0	0.0	72.0	78.0	100.0	164457.0	-1.0	0.0	-1.0	-1.0	-1.0	-1.0	-1.0	164457.0	83.918684	0.996691	83.0	83.0	83.0	85.0	85.0	164457.0	1.000213	1.000003	0.0	0.0	2.0	2.0	2.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.003867	0.287735	0.0	0.0	0.0	0.0	36.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	0.003867	0.287735	0.0	0.0	0.0	0.0	36.0	164457.0	0.003867	0.287735	0.0	0.0	0.0	0.0	36.0	164457.0	20526.033231	1.423597e+06	0.0	0.0	0.0	0.0	117440559.0	164457.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	164457.0	20526.033231	1.423597e+06	0.0	0.0	0.0	0.0	117440559.0	164457.0	20526.033231	1.423597e+06	0.0	0.0	0.0	0.0	117440559.0